long context benchmark
ComplexFuncBench
ComplexFuncBench is a benchmark designed to evaluate large language models' capabilities in handling complex function calling scenarios. It encompasses multi-step and constrained function calling tasks that require long-parameter filling, parameter value reasoning, and managing contexts up to 128k tokens. The benchmark includes 1,000 samples across five real-world scenarios.
Updated Aug 11, 2026
Models7
Model coverage7
MetricScore
EvidenceB
ComplexFuncBench Ranking
Higher score ranks better on this benchmark.
| 01 | OP | 66.5% | 100.0% | 7 | C | |
| 02 | OP | 65.5% | 83.3% | 7 | C | |
| 03 | AM Nova 2 SonicAmazon | 65.2% | 66.7% | 7 | C | |
| 04 | OP | 63.0% | 50.0% | 7 | C | |
| 05 | OP | 49.3% | 33.3% | 7 | C | |
| 06 | OP | 17.6% | 16.7% | 7 | C | |
| 07 | OP | 5.7% | 0.0% | 7 | C |
ComplexFuncBench Score Distribution
A closer view of the leading scores on this benchmark.
ComplexFuncBench Highlights
The leading models and scores on this benchmark.
What is ComplexFuncBench?
What ComplexFuncBench measures and how its scores work.
ComplexFuncBench is a benchmark designed to evaluate large language models' capabilities in handling complex function calling scenarios. It encompasses multi-step and constrained function calling tasks that require long-parameter filling, parameter value reasoning, and managing contexts up to 128k tokens. The benchmark includes 1,000 samples across five real-world scenarios.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- ComplexFuncBench
- Modality
- text
- Primary category
- long context
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- complexfuncbench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about ComplexFuncBench.
Which model scores highest on ComplexFuncBench?
GPT-4o is currently ranked first with 66.5%.
What does ComplexFuncBench measure?
ComplexFuncBench is a benchmark designed to evaluate large language models' capabilities in handling complex function calling scenarios. It encompasses multi-step and constrained function calling tasks that require long-parameter filling, parameter value reasoning, and managing contexts up to 128k tokens. The benchmark includes 1,000 samples across five real-world scenarios.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
7 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.